问题描述：我通过控制台使用tensorflow-gpu没问题，但是通过pycharm使用却不可以，如下所示：
通过控制台：
answer@answer-desktop:/$ python Python 3.7.0 (default, Jun 28 2018, 13:15:42) [GCC 7.2.0] :: Anaconda, Inc. on linux Type "help", "copyright", "credits" or "license" for more information. >>> import tensorflow as tf 2020-02-04 21:37:12.964610: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer.so.6'; dlerror: libnvinfer.so.6: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-10.1/lib64:/usr/local/cuda-10.1/lib64 2020-02-04 21:37:12.964749: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvinfer_plugin.so.6: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-10.1/lib64:/usr/local/cuda-10.1/lib64 2020-02-04 21:37:12.964777: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly. >>> print(tf.test.is_gpu_available()) WARNING:tensorflow:From <stdin>:1: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.config.list_physical_devices('GPU')` instead. 2020-02-04 21:37:37.267421: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 1795795000 Hz 2020-02-04 21:37:37.268461: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55913b67a840 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2020-02-04 21:37:37.268516: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2020-02-04 21:37:37.272139: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2020-02-04 21:37:37.481038: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2020-02-04 21:37:37.481712: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55913b6eb960 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2020-02-04 21:37:37.481755: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): GeForce GTX 1060 3GB, Compute Capability 6.1 2020-02-04 21:37:37.482022: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2020-02-04 21:37:37.482528: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties: pciBusID: 0000:03:00.0 name: GeForce GTX 1060 3GB computeCapability: 6.1 coreClock: 1.7085GHz coreCount: 9 deviceMemorySize: 5.93GiB deviceMemoryBand 178.99GiB/s 2020-02-04 21:37:37.482953: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2020-02-04 21:37:37.485492: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2020-02-04 21:37:37.487486: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2020-02-04 21:37:37.487927: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2020-02-04 21:37:37.490469: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2020-02-04 21:37:37.491950: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2020-02-04 21:37:37.499031: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2020-02-04 21:37:37.499301: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2020-02-04 21:37:37.500387: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2020-02-04 21:37:37.500847: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0 2020-02-04 21:37:37.500941: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2020-02-04 21:37:37.502172: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix: 2020-02-04 21:37:37.502212: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] 0 2020-02-04 21:37:37.502229: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0: N 2020-02-04 21:37:37.502436: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2020-02-04 21:37:37.503003: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2020-02-04 21:37:37.503593: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/device:GPU:0 with 2934 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060 3GB, pci bus id: 0000:03:00.0, compute capability: 6.1) True >>>
返回的True，说明可以
通过pycharm却不行，如下图，返回False
解决办法：
1.修改~/.bashrc
将pycahrm的路径加到环境中，示例如下：
alias pycharm="bash /home/answer/文档/pycharm-professional-2019.3.2/pycharm-2019.3.2/bin/pycharm.sh"
刷新生效：
source ~/.bashrc
2.修改pycharm中的环境变量
选择pycharm 菜单栏Run ——> Run-Edit Configurations ——> Environment variables ——> 将cuda的路径加进去 例如：LD_LIBRARY_PATH=/usr/local/cuda-10.1/lib64
在运行就可以了